What if we could use the data from fevered searches for flu information on the Web, plus humidity observations, to help predict the course of an outbreak? If new research lives up to its promise, we’ll soon be able to do just that.
The rapid growth in science journals has produced an avalanche of literature that keeps researchers scrambling to keep up. Underneath, there’s an even larger buildup of supporting data. Experts met at UCAR to consider best practices for citing this ever-growing pool of data.
Paradata—information on how people access and share information through social media—could play a big role in assessing the usefulness of educational resources in the university setting, according to Susan Van Gundy.
There’s much more to wind energy than throwing a few turbines up and watching the blades spin and the cash roll in. NCAR and partners are adding rigor and efficiency to wind power prediction and resource assessment.
The growing array of tools at the disposal of climate scientists doesn’t necessarily make life any easier for them. Each set of data has its idiosyncrasies, some of which aren’t evident at first glance.
Unidata celebrated its 25th anniversary on 15-16 October with a rare gathering of staff, founders, partners, and collaborators from around the country. Attendees celebrated the program's accomplishments and looked ahead to the future.
Doug Nychka, NCAR's Institute for Mathematics Applied to the Geosciences • A statistician by training, Doug leads IMAGe in its mission to bring mathematical models and tools to bear on fundamental problems in the geosciences.
Tim Scheitlin, NCAR's Computational Information Systems Laboratory • "One of the most rewarding things about this job is taking scientific data and making it visually interesting while preserving scientific accuracy," Scheitlin says.
Jielun Sun, NCAR's Mesoscale and Microscale Meteorology Division • Sun likens data analysis to a form of meditation. "It's all about discovery," she explains. "Every time I look at data, I see something and feel like I learn things."
Claudia Tebaldi, NCAR's Institute for Mathematics Applied to Geosciences • One of Claudia's favorite things about her job is working closely with the scientists who interpret the data that she analyzes. "Because I'm a statistician, I couldn't be anything but a team player," she points out.